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In this paper, we present a method to use advance demand information (ADI), taking the form of request for quotation (RFQ) data, in B2B sales forecasting. We apply supervised machine learning and Natural Language Processing techniques to analyze and learn from RFQs. We apply and test our approach in a case study at a large after-sales service and maintenance provider. After evaluation we found that our approach identifies ~ 70% of actual sales (recall) with a precision rate of ~ 50%, whichdoi:10.1016/j.eswa.2021.115925 fatcat:oj3fctzm7fh3xessegfck6ts7m